Different sedimentary zones in coral reefs lead to significant anisotropy in the pore structure of coral reef limestone(CRL),making it difficult to study mechanical behaviors.With X-ray computed tomography(CT),112 CRL...Different sedimentary zones in coral reefs lead to significant anisotropy in the pore structure of coral reef limestone(CRL),making it difficult to study mechanical behaviors.With X-ray computed tomography(CT),112 CRL samples were utilized for training the support vector machine(SVM)-,random forest(RF)-,and back propagation neural network(BPNN)-based models,respectively.Simultaneously,the machine learning model was embedded into genetic algorithm(GA)for parameter optimization to effectively predict uniaxial compressive strength(UCS)of CRL.Results indicate that the BPNN model with five hidden layers presents the best training effect in the data set of CRL.The SVM-based model shows a tendency to overfitting in the training set and poor generalization ability in the testing set.The RF-based model is suitable for training CRL samples with large data.Analysis of Pearson correlation coefficient matrix and the percentage increment method of performance metrics shows that the dry density,pore structure,and porosity of CRL are strongly correlated to UCS.However,the P-wave velocity is almost uncorrelated to the UCS,which is significantly distinct from the law for homogenous geomaterials.In addition,the pore tensor proposed in this paper can effectively reflect the pore structure of coral framework limestone(CFL)and coral boulder limestone(CBL),realizing the quantitative characterization of the heterogeneity and anisotropy of pore.The pore tensor provides a feasible idea to establish the relationship between pore structure and mechanical behavior of CRL.展开更多
This letter comments on the article that developed and tested a machine learning model that predicts lymphovascular invasion/perineural invasion status by combining clinical indications and spectral computed tomograph...This letter comments on the article that developed and tested a machine learning model that predicts lymphovascular invasion/perineural invasion status by combining clinical indications and spectral computed tomography characteristics accurately.We review the research content,methodology,conclusions,strengths and weaknesses of the study,and introduce follow-up research to this work.展开更多
BACKGROUND Vascular and nerve infiltration are important indicators for the progression and prognosis of gastric cancer(GC),but traditional imaging methods have some limitations in preoperative evaluation.In recent ye...BACKGROUND Vascular and nerve infiltration are important indicators for the progression and prognosis of gastric cancer(GC),but traditional imaging methods have some limitations in preoperative evaluation.In recent years,energy spectrum computed tomography(CT)multiparameter imaging technology has been gradually applied in clinical practice because of its advantages in tissue contrast and lesion detail display.AIM To explore and analyze the value of multiparameter energy spectrum CT imaging in the preoperative assessment of vascular invasion(LVI)and nerve invasion(PNI)in GC patients.METHODS Data from 62 patients with GC confirmed by pathology and accompanied by energy spectrum CT scanning at our hospital between September 2022 and September 2023,including 46 males and 16 females aged 36-71(57.5±9.1)years,were retrospectively collected.The patients were divided into a positive group(42 patients)and a negative group(20 patients)according to the presence of LVI/PNI.The CT values(CT40 keV,CT70 keV),iodine concentration(IC),and normalized IC(NIC)of lesions in the upper energy spectrum CT images of the arterial phase,venous phase,and delayed phase 40 and 70 keV were measured,and the slopes of the energy spectrum curves[K(40-70)]from 40 to 70 keV were calculated.Arterial Core Tip:To investigate the application value of multiparameter energy spectrum computed tomography(CT)imaging in the preoperative assessment of vascular and nerve infiltration in patients with gastric cancer(GC).The imaging data of GC patients were retrospectively analyzed to evaluate the accuracy and sensitivity of CT for identifying and quantifying vascular and nerve infiltration and for comparison with postoperative pathological results.The purpose of this study was to verify the clinical feasibility and potential advantages of multiparameter energy spectrum CT imaging in guiding preoperative diagnosis and treatment decision-making and to provide a new imaging basis for improving the diagnostic accuracy and prognosis of GC patients.展开更多
BACKGROUND Neoadjuvant chemotherapy(NAC)has become the standard care for advanced adenocarcinoma of esophagogastric junction(AEG),although a part of the patients cannot benefit from NAC.There are no models based on ba...BACKGROUND Neoadjuvant chemotherapy(NAC)has become the standard care for advanced adenocarcinoma of esophagogastric junction(AEG),although a part of the patients cannot benefit from NAC.There are no models based on baseline computed tomography(CT)to predict response of Siewert type II or III AEG to NAC with docetaxel,oxaliplatin and S-1(DOS).AIM To develop a CT-based nomogram to predict response of Siewert type II/III AEG to NAC with DOS.METHODS One hundred and twenty-eight consecutive patients with confirmed Siewert type II/III AEG underwent CT before and after three cycles of NAC with DOS,and were randomly and consecutively assigned to the training cohort(TC)(n=94)and the validation cohort(VC)(n=34).Therapeutic effect was assessed by disease-control rate and progressive disease according to the Response Evaluation Criteria in Solid Tumors(version 1.1)criteria.Possible prognostic factors associated with responses after DOS treatment including Siewert classification,gross tumor volume(GTV),and cT and cN stages were evaluated using pretherapeutic CT data in addition to sex and age.Univariate and multivariate analyses of CT and clinical features in the TC were performed to determine independent factors associated with response to DOS.A nomogram was established based on independent factors to predict the response.The predictive performance of the nomogram was evaluated by Concordance index(C-index),calibration and receiver operating characteristics curve in the TC and VC.RESULTS Univariate analysis showed that Siewert type(52/55 vs 29/39,P=0.005),pretherapeutic cT stage(57/62 vs 24/32,P=0.028),GTV(47.3±27.4 vs 73.2±54.3,P=0.040)were significantly associated with response to DOS in the TC.Multivariate analysis of the TC also showed that the pretherapeutic cT stage,GTV and Siewert type were independent predictive factors related to response to DOS(odds ratio=4.631,1.027 and 7.639,respectively;all P<0.05).The nomogram developed with these independent factors showed an excellent performance to predict response to DOS in the TC and VC(C-index:0.838 and 0.824),with area under the receiver operating characteristic curve of 0.838 and 0.824,respectively.The calibration curves showed that the practical and predicted response to DOS effectively coincided.CONCLUSION A novel nomogram developed with pretherapeutic cT stage,GTV and Siewert type predicted the response of Siewert type II/III AEG to NAC with DOS.展开更多
BACKGROUND The prognosis for hepatocellular carcinoma(HCC)in the presence of cirrhosis is unfavourable,primarily attributable to the high incidence of recurrence.AIM To develop a machine learning model for predicting ...BACKGROUND The prognosis for hepatocellular carcinoma(HCC)in the presence of cirrhosis is unfavourable,primarily attributable to the high incidence of recurrence.AIM To develop a machine learning model for predicting early recurrence(ER)of posthepatectomy HCC in patients with cirrhosis and to stratify patients’overall survival(OS)based on the predicted risk of recurrence.METHODS In this retrospective study,214 HCC patients with cirrhosis who underwent curative hepatectomy were examined.Radiomics feature selection was conducted using the least absolute shrinkage and selection operator and recursive feature elimination methods.Clinical-radiologic features were selected through univariate and multivariate logistic regression analyses.Five machine learning methods were used for model comparison,aiming to identify the optimal model.The model’s performance was evaluated using the receiver operating characteristic curve[area under the curve(AUC)],calibration,and decision curve analysis.Additionally,the Kaplan-Meier(K-M)curve was used to evaluate the stratification effect of the model on patient OS.RESULTS Within this study,the most effective predictive performance for ER of post-hepatectomy HCC in the background of cirrhosis was demonstrated by a model that integrated radiomics features and clinical-radiologic features.In the training cohort,this model attained an AUC of 0.844,while in the validation cohort,it achieved a value of 0.790.The K-M curves illustrated that the combined model not only facilitated risk stratification but also exhibited significant discriminatory ability concerning patients’OS.CONCLUSION The combined model,integrating both radiomics and clinical-radiologic characteristics,exhibited excellent performance in HCC with cirrhosis.The K-M curves assessing OS revealed statistically significant differences.展开更多
BACKGROUND Neoadjuvant immunochemotherapy(nICT)has emerged as a popular treatment approach for advanced gastric cancer(AGC)in clinical practice worldwide.However,the response of AGC patients to nICT displays significa...BACKGROUND Neoadjuvant immunochemotherapy(nICT)has emerged as a popular treatment approach for advanced gastric cancer(AGC)in clinical practice worldwide.However,the response of AGC patients to nICT displays significant heterogeneity,and no existing radiomic model utilizes baseline computed tomography to predict treatment outcomes.AIM To establish a radiomic model to predict the response of AGC patients to nICT.METHODS Patients with AGC who received nICT(n=60)were randomly assigned to a training cohort(n=42)or a test cohort(n=18).Various machine learning models were developed using selected radiomic features and clinical risk factors to predict the response of AGC patients to nICT.An individual radiomic nomogram was established based on the chosen radiomic signature and clinical signature.The performance of all the models was assessed through receiver operating characteristic curve analysis,decision curve analysis(DCA)and the Hosmer Lemeshow goodness-of-fit test.RESULTS The radiomic nomogram could accurately predict the response of AGC patients to nICT.In the test cohort,the area under curve was 0.893,with a 95%confidence interval of 0.803-0.991.DCA indicated that the clinical application of the radiomic nomogram yielded greater net benefit than alternative models.CONCLUSION A nomogram combining a radiomic signature and a clinical signature was designed to predict the efficacy of nICT in patients with AGC.This tool can assist clinicians in treatment-related decision-making.展开更多
BACKGROUND Gastrointestinal stromal tumors(GIST)are prevalent neoplasm originating from the gastrointestinal mesenchyme.Approximately 50%of GIST patients experience tumor recurrence within 5 years.Thus,there is a pres...BACKGROUND Gastrointestinal stromal tumors(GIST)are prevalent neoplasm originating from the gastrointestinal mesenchyme.Approximately 50%of GIST patients experience tumor recurrence within 5 years.Thus,there is a pressing need to accurately evaluate risk stratification preoperatively.AIM To assess the application of a deep learning model(DLM)combined with computed tomography features for predicting risk stratification of GISTs.METHODS Preoperative contrast-enhanced computed tomography(CECT)images of 551 GIST patients were retrospectively analyzed.All image features were independently analyzed by two radiologists.Quantitative parameters were statistically analyzed to identify significant predictors of high-risk malignancy.Patients were randomly assigned to the training(n=386)and validation cohorts(n=165).A DLM and a combined DLM were established for predicting the GIST risk stratification using convolutional neural network and subsequently evaluated in the validation cohort.RESULTS Among the analyzed CECT image features,tumor size,ulceration,and enlarged feeding vessels were identified as significant risk predictors(P<0.05).In DLM,the overall area under the receiver operating characteristic curve(AUROC)was 0.88,with the accuracy(ACC)and AUROCs for each stratification being 87%and 0.96 for low-risk,79%and 0.74 for intermediate-risk,and 84%and 0.90 for high-risk,respectively.The overall ACC and AUROC were 84%and 0.94 in the combined model.The ACC and AUROCs for each risk stratification were 92%and 0.97 for low-risk,87%and 0.83 for intermediate-risk,and 90%and 0.96 for high-risk,respectively.Differences in AUROCs for each risk stratification between the two models were significant(P<0.05).CONCLUSION A combined DLM with satisfactory performance for preoperatively predicting GIST stratifications was developed using routine computed tomography data,demonstrating superiority compared to DLM.展开更多
BACKGROUND Percutaneous endoscopic lumbar decompression(PELD)shows promise for lumbar spinal stenosis(LSS)treatment,but its use is limited by the disease's complexity and procedural challenges.AIM In this study,th...BACKGROUND Percutaneous endoscopic lumbar decompression(PELD)shows promise for lumbar spinal stenosis(LSS)treatment,but its use is limited by the disease's complexity and procedural challenges.AIM In this study,the effects of preoperative planning and intraoperative guidance with computed tomography(CT)/magnetic resonance imaging(MRI)registration techniques on PELD for LSS and postoperative rehabilitation outcomes were evaluated.METHODS This retrospective study was conducted with data from patients who underwent PELD for LSS between January 2021 and December 2023.Patients were assigned to preoperative CT/MRI registration and control groups.Data collected included the operative time,length of hospital stay,visual analog scale(VAS)scores for low back and leg pain,and the Japanese Orthopaedic Association(JOA)lumbar spine score.Differences between groups were assessed using Student’s t test.RESULTS Data from 135 patients(71 in the CT/MRI registration group,64 in the control group)were analyzed.The operative time was significantly shorter in the CT/MRI registration group(P=0.007).At 2 months postoperatively,both groups showed significant reductions in VAS leg and low back pain scores(all P<0.001)and improvements in the JOA score(both P<0.001).No complication or death occurred.Preoperatively,pain and JOA scores were similar between groups(P=0.830,P=0.470,and P=0.287,respectively).At 2 months postoperatively,patients in the CT/MRI registration group reported lower leg and low back pain levels(P<0.001 and P=0.001,respectively)and had higher JOA scores(P=0.004)than did patients in the control group.CONCLUSION Preoperative CT/MRI registration for PELD for LSS reduced the operative time and VAS pain scores at 2 months and improved JOA scores,demonstrating enhanced effectiveness and safety.展开更多
X-ray computed tomography(XCT)has recently emerged as a powerful tool for characterizing the evolution of microstructure during phase transformation in three dimensional(3D)such as dendritic solidification of alloys.T...X-ray computed tomography(XCT)has recently emerged as a powerful tool for characterizing the evolution of microstructure during phase transformation in three dimensional(3D)such as dendritic solidification of alloys.This paper briefly reviews the recent advances in the in-situ observation of aluminium alloys,magnesium alloys and nickel-based superalloys during solidification using laboratory XCT and synchrotron X-ray sources.The focus is on the growth kinetics of dendrites,porosity and secondary phases.In addition,in-situ characterization during the loading and corrosion process is also discussed.展开更多
BACKGROUND Ankle fractures are common lesions of the lower limbs.Approximately 40%of ankle fractures affect the posterior malleolus(PM).Historically,PM osteosynthesis was recommended when PM size in X-ray images was g...BACKGROUND Ankle fractures are common lesions of the lower limbs.Approximately 40%of ankle fractures affect the posterior malleolus(PM).Historically,PM osteosynthesis was recommended when PM size in X-ray images was greater than 25%of the joint.Currently,computed tomography(CT)has been gaining traction in the preoperative evaluation of ankle fractures.AIM To elucidate the similarity in dimensions and to correlate PM size in X-ray images with the articular surface of the affected tibial plafond in the axial view on CT(AXCT)of a PM fracture.METHODS Eighty-one patients(mean age:39.4±13.5 years)were evaluated(54.3%were male).Two independent examiners measured PM size in profile X-ray images(PMXR)and sagittal CT(SAGCT)slices.The correlation of the measurements between the examiners and the difference in the PM fragment sizes between the two images were compared.Next,the PM size in PMXR was compared with the surface of the tibial plafond involved in the fracture in AXCT according to the Haraguchi classification.RESULTS The correlation rates between the examiners were 0.93 and 0.94 for PMXR and SAGCT,respectively(P<0.001).Fragments were 2.12%larger in SAGCT than in PMXR(P=0.018).In PMXR,there were 56 cases<25%and 25 cases≥25%.When PMXR was<25%,AXCT corresponded to 10.13%of the tibial plafond.When PMXR was≥25%,AXCT was 24.52%(P<0.001).According to the Haraguchi classification,fracture types I and II had similar PMXR measurements that were greater than those of type III.When analyzing AXCT,a significant difference was found between the three types,with II>I>III(P<0.001).CONCLUSION PM fractures show different sizes using X-ray or CT images.CT showed a larger PM in the sagittal plane and allowed the visualization of the real dimensions of the tibial plafond surface.展开更多
BACKGROUND Pancreatic neuroendocrine tumors(NETs)account for about 1%–2%of pancreatic tumors and about 8%of all NETs.Computed tomography(CT),magnetic resonance imaging,and endoscopic ultrasound are common imaging mod...BACKGROUND Pancreatic neuroendocrine tumors(NETs)account for about 1%–2%of pancreatic tumors and about 8%of all NETs.Computed tomography(CT),magnetic resonance imaging,and endoscopic ultrasound are common imaging modalities for the diagnosis of pancreatic NETs.Furthermore,somatostatin receptor imaging is of great value for diagnosing pancreatic NETs.Herein,we report the efficacy of technetium-99m methoxy-2-isobutylisonitrile(99mTc-MIBI)single photon emission CT(SPECT)/CT for detecting pancreatic NETs.CASE SUMMARY A 57-year-old woman presented to our hospital with a 1-d history of persistent upper abdominal distending pain.The distending pain in the upper abdomen was aggravated after eating,with nausea and retching.Routine blood test results showed a high neutrophil percentage,low leukomonocyte and monocyte percentages,and low leukomonocyte and eosinophil counts.Amylase,liver and kidney function,and tumor markers alpha-fetoprotein,carcinoembryonic antigen,and cancer antigen(CA)125,CA72-4,CA19-9,and CA153 were normal.Abdominal CT showed a mass,with multiple calcifications between the pancreas and the spleen.The boundary between the mass and the pancreas and spleen was poorly defined.Contrast-enhanced CT revealed that the upper abdominal mass was unevenly and gradually enhanced.99mTc-MIBI SPECT/CT revealed that a focal radioactive concentration,with mild radioactive concentration extending into the upper abdominal mass,was present at the pancreatic body and tail.The 99mTc-MIBI SPECT/CT manifestations were consistent with the final pathological diagnosis of pancreatic NET.CONCLUSION 99mTc-MIBI SPECT/CT appears to be a valuable tool for detecting pancreatic NETs.展开更多
Computed tomography(CT)is emerging as a prominent diagnostic modality in the field of cardiovascular imaging.Artificial intelligence(AI)is making significant strides in the field of information technology,the commerci...Computed tomography(CT)is emerging as a prominent diagnostic modality in the field of cardiovascular imaging.Artificial intelligence(AI)is making significant strides in the field of information technology,the commercial industry,and health care.Machine learning(ML),a branch of AI,can optimize the performance of CT and augment the assessment of coronary artery disease.These ML platforms can automate multiple tasks,perform calculations,and integrate information from a variety of data sources.In this review article,we explore the ML in CT imaging.展开更多
Coronary artery disease(CAD)has become a major illness endangering human health.It mainly manifests as atherosclerotic plaques,especially vulnerable plaques without obvious symptoms in the early stage.Once a rupture o...Coronary artery disease(CAD)has become a major illness endangering human health.It mainly manifests as atherosclerotic plaques,especially vulnerable plaques without obvious symptoms in the early stage.Once a rupture occurs,it will lead to severe coronary stenosis,which in turn may trigger a major adverse cardiovascular event.Computed tomography angiography(CTA)has become a standard diagnostic tool for early screening of coronary plaque and stenosis due to its advantages in high resolution,noninvasiveness,and three-dimensional imaging.However,manual examination of CTA images by radiologists has been proven to be tedious and time-consuming,which might also lead to intra-and interobserver errors.Nowadays,many machine learning algorithms have enabled the(semi-)automatic diagnosis of CAD by extracting quantitative features from CTA images.This paper provides a survey of these machine learning algorithms for the diagnosis of CAD in CTA images,including coronary artery extraction,coronary plaque detection,vulnerable plaque identification,and coronary stenosis assessment.Most included articles were published within this decade and are found in the Web of Science.We wish to give readers a glimpse of the current status,challenges,and perspectives of these machine learning-based analysis methods for automatic CAD diagnosis.展开更多
BACKGROUND The preoperative prediction of peritoneal metastasis(PM)in gastric cancer would prevent unnecessary surgery and promptly indicate an appropriate treatment plan.AIM To explore the predictive value of viscera...BACKGROUND The preoperative prediction of peritoneal metastasis(PM)in gastric cancer would prevent unnecessary surgery and promptly indicate an appropriate treatment plan.AIM To explore the predictive value of visceral fat(VF)parameters obtained from preoperative computed tomography(CT)images for occult PM and to develop an individualized model for predicting occult PM in patients with gastric carcinoma(GC).METHODS A total of 128 confirmed GC cases(84 male and 44 female patients)that underwent CT scans were analyzed and categorized into PM-positive(n=43)and PM-negative(n=85)groups.The clinical characteristics and VF parameters of two regions of interest(ROIs)were collected.Univariate and stratified analyses based on VF volume were performed to screen for predictive characteristics for occult PM.Prediction models with and without VF parameters were established by multivariable logistic regression analysis.RESULTS The mean attenuations of VF_(ROI 1)and VF_(ROI 2)varied significantly between the PM-positive and PMnegative groups(P=0.044 and 0.001,respectively).The areas under the receiver operating characteristic curves(AUCs)of VF_(ROI 1)and VF_(ROI 2)were 0.599 and 0.657,respectively.The mean attenuation of VF_(ROI 2)was included in the final prediction combined model,but not an independent risk factor of PM(P=0.068).No significant difference was observed between the models with and without mean attenuation of VF(AUC:0.749 vs 0.730,P=0.339).CONCLUSION The mean attenuation of VF is a potential auxiliary parameter for predicting occult PM in patients with GC.展开更多
A small problem about soil particle regularization and contacts but essential to geotechnical engineering was studied.The soils sourced from Guangzhou and Xiamen were sieved into five different particle scale ranges(d...A small problem about soil particle regularization and contacts but essential to geotechnical engineering was studied.The soils sourced from Guangzhou and Xiamen were sieved into five different particle scale ranges(d<0.075 mm,0.075 mm≤d<0.1 mm,0.1 mm≤d<0.2 mm,0.2 mm≤d<0.5 mm and 0.5 mm≤d<1.0 mm)to study the structures and particle contacts of granite residual soil.The X-ray micro computed tomography method was used to reconstruct the microstructure of granite residual soil.The particle was identified and regularized using principal component analysis(PCA).The particle contacts and geometrical characteristics in 3D space were analyzed and summarized using statistical analyses.The results demonstrate that the main types of contact among the particles are face-face,face-angle,face-edge,edge-edge,edge-angle and angle-angle contacts for particle sizes less than 0.2 mm.When the particle sizes are greater than 0.2 mm,the contacts are effectively summarized as face-face,face-angle,face-edge,edge-edge,edge-angle,angle-angle,sphere-sphere,sphere-face,sphere-edge and sphere-angle contacts.The differences in porosity among the original sample,reconstructed sample and regularized sample are closely related to the water-swelling and water-disintegrable characteristics of granite residual soil.展开更多
Mineral dissemination and pore space distribution in ore particles are important features that influence heap leaching performance. To quantify the mineral dissemination and pore space distribution of an ore particle,...Mineral dissemination and pore space distribution in ore particles are important features that influence heap leaching performance. To quantify the mineral dissemination and pore space distribution of an ore particle, a cylindrical copper oxide ore sample (I center dot 4.6 mm x 5.6 mm) was scanned using high-resolution X-ray computed tomography (HRXCT), a nondestructive imaging technology, at a spatial resolution of 4.85 mu m. Combined with three-dimensional (3D) image analysis techniques, the main mineral phases and pore space were segmented and the volume fraction of each phase was calculated. In addition, the mass fraction of each mineral phase was estimated and the result was validated with that obtained using traditional techniques. Furthermore, the pore phase features, including the pore size distribution, pore surface area, pore fractal dimension, pore centerline, and the pore connectivity, were investigated quantitatively. The pore space analysis results indicate that the pore size distribution closely fits a log-normal distribution and that the pore space morphology is complicated, with a large surface area and low connectivity. This study demonstrates that the combination of HRXCT and 3D image analysis is an effective tool for acquiring 3D mineralogical and pore structural data.展开更多
Due to seasonal climate alterations,the microstructure and permeability of granite residual soil are easily affected by multiple dry-wet cycles.The X-ray micro computed tomography(micro-CT)acted as a nondestructive to...Due to seasonal climate alterations,the microstructure and permeability of granite residual soil are easily affected by multiple dry-wet cycles.The X-ray micro computed tomography(micro-CT)acted as a nondestructive tool for characterizing the microstructure of soil samples exposed to a range of damage levels induced by dry-wet cycles.Subsequently,the variations of pore distribution and permeability due to drywet cycling effects were revealed based on three-dimensional(3D)pore distribution analysis and seepage simulations.According to the results,granite residual soils could be separated into four different components,namely,pores,clay,quartz,and hematite,from micro-CT images.The reconstructed 3D pore models dynamically demonstrated the expanding and connecting patterns of pore structures during drywet cycles.The values of porosity and connectivity are positively correlated with the number of dry-wet cycles,which were expressed by exponential and linear functions,respectively.The pore volume probability distribution curves of granite residual soil coincide with the χ^(2)distribution curve,which verifies the effectiveness of the assumption of χ^(2)distribution probability.The pore volume distribution curves suggest that the pores in soils were divided into four types based on their volumes,i.e.micropores,mesopores,macropores,and cracks.From a quantitative and visual perspective,considerable small pores are gradually transformed into cracks with a large volume and a high connectivity.Under the action of dry-wet cycles,the number of seepage flow streamlines which contribute to water permeation in seepage simulation increases distinctly,as well as the permeability and hydraulic conductivity.The calculated hydraulic conductivity is comparable with measured ones with an acceptable error margin in general,verifying the accuracy of seepage simulations based on micro-CT results.展开更多
The bio-sandstone, which was cemented by microbe cement, was firstly prepared, and then the microstructure evolution process was studied by X-ray computed tomography （X-CT） technique. The experimental results indica...The bio-sandstone, which was cemented by microbe cement, was firstly prepared, and then the microstructure evolution process was studied by X-ray computed tomography （X-CT） technique. The experimental results indicate that the microstructure of bio-sandstone becomes dense with the development of age. The evolution of inner structure at different positions is different due to the different contents of microbial induced precipitation calcite. Besides, the increase rate of microbial induced precipitation calcite gradually decreases because of the reduction of microbe absorption content with the decreasing pore size in bio-sandstone.展开更多
As healthcare professionals continue to combat the coronavirus disease 2019(COVID-19)infection worldwide,there is an increasing interest in the role of imaging and the relevance of various modalities.Since imaging not...As healthcare professionals continue to combat the coronavirus disease 2019(COVID-19)infection worldwide,there is an increasing interest in the role of imaging and the relevance of various modalities.Since imaging not only helps assess the disease at the time of diagnosis but also aids evaluation of response to management,it is critical to examine the role of different modalities currently in use,such as baseline X-rays and computed tomography scans carefully.In this article,we will draw attention to the critical findings for the radiologist.Further,we will look at point of care ultrasound,an increasingly a popular tool in diagnostic medicine,as a component of COVID-19 management.展开更多
The three dimensional （3D） geometry of soil macropores largely controls preferential flow, which is a significant infiltrating mechanism for rainfall in forest soils and affects slope stability. However, detailed st...The three dimensional （3D） geometry of soil macropores largely controls preferential flow, which is a significant infiltrating mechanism for rainfall in forest soils and affects slope stability. However, detailed studies on the 3D geometry of macropore networks in forest soils are rare. The intense rainfall-triggered potentially unstable slopes were threatening the villages at the downstream of Touzhai valley （Yunnan, China）. We visualized and quantified the 3D macropore networks in undisturbed soil columns （Histosols） taken from a forest hillslope in Touzhai valley, and compared them with those in agricultural soils （corn and soybean in USA; barley, fodder beet and red fescue in Denmark） and grassland soils in USA. We took two large undisturbed soil columns （250 mm^25o mmxsoo mm）, and scanned the soil columns at in-situ soil water content conditions using X-ray computed tomography at a voxel resolution of 0.945 × 0.945 × 1.500o mm^3. After reconstruction and visualization, we quantified the characteristics of macropore networks. In the studied forest soils, the main types of maeropores were root channels, inter-aggregate voids, maeropores without knowing origin, root-soil interfaee and stone-soil interface. While maeropore networks tend to be more eomplex, larger, deeper and longer. The forest soils have high maeroporosity, total maeropore wall area density, node density, and large maeropore volume, hydraulie radius, mean maeropore length, angle, and low tortuosity. The findings suggest that maeropore networks in the forest soils have high inter- connectivity, vertical continuity, linearity and less vertically oriented.展开更多
基金supported by the National Natural Science Foundation of China(Grant Nos.41877267 and 41877260)the Priority Research Program of the Chinese Academy of Sciences(Grant No.XDA13010201).
文摘Different sedimentary zones in coral reefs lead to significant anisotropy in the pore structure of coral reef limestone(CRL),making it difficult to study mechanical behaviors.With X-ray computed tomography(CT),112 CRL samples were utilized for training the support vector machine(SVM)-,random forest(RF)-,and back propagation neural network(BPNN)-based models,respectively.Simultaneously,the machine learning model was embedded into genetic algorithm(GA)for parameter optimization to effectively predict uniaxial compressive strength(UCS)of CRL.Results indicate that the BPNN model with five hidden layers presents the best training effect in the data set of CRL.The SVM-based model shows a tendency to overfitting in the training set and poor generalization ability in the testing set.The RF-based model is suitable for training CRL samples with large data.Analysis of Pearson correlation coefficient matrix and the percentage increment method of performance metrics shows that the dry density,pore structure,and porosity of CRL are strongly correlated to UCS.However,the P-wave velocity is almost uncorrelated to the UCS,which is significantly distinct from the law for homogenous geomaterials.In addition,the pore tensor proposed in this paper can effectively reflect the pore structure of coral framework limestone(CFL)and coral boulder limestone(CBL),realizing the quantitative characterization of the heterogeneity and anisotropy of pore.The pore tensor provides a feasible idea to establish the relationship between pore structure and mechanical behavior of CRL.
文摘This letter comments on the article that developed and tested a machine learning model that predicts lymphovascular invasion/perineural invasion status by combining clinical indications and spectral computed tomography characteristics accurately.We review the research content,methodology,conclusions,strengths and weaknesses of the study,and introduce follow-up research to this work.
文摘BACKGROUND Vascular and nerve infiltration are important indicators for the progression and prognosis of gastric cancer(GC),but traditional imaging methods have some limitations in preoperative evaluation.In recent years,energy spectrum computed tomography(CT)multiparameter imaging technology has been gradually applied in clinical practice because of its advantages in tissue contrast and lesion detail display.AIM To explore and analyze the value of multiparameter energy spectrum CT imaging in the preoperative assessment of vascular invasion(LVI)and nerve invasion(PNI)in GC patients.METHODS Data from 62 patients with GC confirmed by pathology and accompanied by energy spectrum CT scanning at our hospital between September 2022 and September 2023,including 46 males and 16 females aged 36-71(57.5±9.1)years,were retrospectively collected.The patients were divided into a positive group(42 patients)and a negative group(20 patients)according to the presence of LVI/PNI.The CT values(CT40 keV,CT70 keV),iodine concentration(IC),and normalized IC(NIC)of lesions in the upper energy spectrum CT images of the arterial phase,venous phase,and delayed phase 40 and 70 keV were measured,and the slopes of the energy spectrum curves[K(40-70)]from 40 to 70 keV were calculated.Arterial Core Tip:To investigate the application value of multiparameter energy spectrum computed tomography(CT)imaging in the preoperative assessment of vascular and nerve infiltration in patients with gastric cancer(GC).The imaging data of GC patients were retrospectively analyzed to evaluate the accuracy and sensitivity of CT for identifying and quantifying vascular and nerve infiltration and for comparison with postoperative pathological results.The purpose of this study was to verify the clinical feasibility and potential advantages of multiparameter energy spectrum CT imaging in guiding preoperative diagnosis and treatment decision-making and to provide a new imaging basis for improving the diagnostic accuracy and prognosis of GC patients.
文摘BACKGROUND Neoadjuvant chemotherapy(NAC)has become the standard care for advanced adenocarcinoma of esophagogastric junction(AEG),although a part of the patients cannot benefit from NAC.There are no models based on baseline computed tomography(CT)to predict response of Siewert type II or III AEG to NAC with docetaxel,oxaliplatin and S-1(DOS).AIM To develop a CT-based nomogram to predict response of Siewert type II/III AEG to NAC with DOS.METHODS One hundred and twenty-eight consecutive patients with confirmed Siewert type II/III AEG underwent CT before and after three cycles of NAC with DOS,and were randomly and consecutively assigned to the training cohort(TC)(n=94)and the validation cohort(VC)(n=34).Therapeutic effect was assessed by disease-control rate and progressive disease according to the Response Evaluation Criteria in Solid Tumors(version 1.1)criteria.Possible prognostic factors associated with responses after DOS treatment including Siewert classification,gross tumor volume(GTV),and cT and cN stages were evaluated using pretherapeutic CT data in addition to sex and age.Univariate and multivariate analyses of CT and clinical features in the TC were performed to determine independent factors associated with response to DOS.A nomogram was established based on independent factors to predict the response.The predictive performance of the nomogram was evaluated by Concordance index(C-index),calibration and receiver operating characteristics curve in the TC and VC.RESULTS Univariate analysis showed that Siewert type(52/55 vs 29/39,P=0.005),pretherapeutic cT stage(57/62 vs 24/32,P=0.028),GTV(47.3±27.4 vs 73.2±54.3,P=0.040)were significantly associated with response to DOS in the TC.Multivariate analysis of the TC also showed that the pretherapeutic cT stage,GTV and Siewert type were independent predictive factors related to response to DOS(odds ratio=4.631,1.027 and 7.639,respectively;all P<0.05).The nomogram developed with these independent factors showed an excellent performance to predict response to DOS in the TC and VC(C-index:0.838 and 0.824),with area under the receiver operating characteristic curve of 0.838 and 0.824,respectively.The calibration curves showed that the practical and predicted response to DOS effectively coincided.CONCLUSION A novel nomogram developed with pretherapeutic cT stage,GTV and Siewert type predicted the response of Siewert type II/III AEG to NAC with DOS.
基金Supported by Anhui Provincial Key Research and Development Plan,No.202104j07020048.
文摘BACKGROUND The prognosis for hepatocellular carcinoma(HCC)in the presence of cirrhosis is unfavourable,primarily attributable to the high incidence of recurrence.AIM To develop a machine learning model for predicting early recurrence(ER)of posthepatectomy HCC in patients with cirrhosis and to stratify patients’overall survival(OS)based on the predicted risk of recurrence.METHODS In this retrospective study,214 HCC patients with cirrhosis who underwent curative hepatectomy were examined.Radiomics feature selection was conducted using the least absolute shrinkage and selection operator and recursive feature elimination methods.Clinical-radiologic features were selected through univariate and multivariate logistic regression analyses.Five machine learning methods were used for model comparison,aiming to identify the optimal model.The model’s performance was evaluated using the receiver operating characteristic curve[area under the curve(AUC)],calibration,and decision curve analysis.Additionally,the Kaplan-Meier(K-M)curve was used to evaluate the stratification effect of the model on patient OS.RESULTS Within this study,the most effective predictive performance for ER of post-hepatectomy HCC in the background of cirrhosis was demonstrated by a model that integrated radiomics features and clinical-radiologic features.In the training cohort,this model attained an AUC of 0.844,while in the validation cohort,it achieved a value of 0.790.The K-M curves illustrated that the combined model not only facilitated risk stratification but also exhibited significant discriminatory ability concerning patients’OS.CONCLUSION The combined model,integrating both radiomics and clinical-radiologic characteristics,exhibited excellent performance in HCC with cirrhosis.The K-M curves assessing OS revealed statistically significant differences.
基金Supported by the Affiliated Hospital of Qingdao University Horizontal Fund,No.3635Intramural Project Fund,No.4618.
文摘BACKGROUND Neoadjuvant immunochemotherapy(nICT)has emerged as a popular treatment approach for advanced gastric cancer(AGC)in clinical practice worldwide.However,the response of AGC patients to nICT displays significant heterogeneity,and no existing radiomic model utilizes baseline computed tomography to predict treatment outcomes.AIM To establish a radiomic model to predict the response of AGC patients to nICT.METHODS Patients with AGC who received nICT(n=60)were randomly assigned to a training cohort(n=42)or a test cohort(n=18).Various machine learning models were developed using selected radiomic features and clinical risk factors to predict the response of AGC patients to nICT.An individual radiomic nomogram was established based on the chosen radiomic signature and clinical signature.The performance of all the models was assessed through receiver operating characteristic curve analysis,decision curve analysis(DCA)and the Hosmer Lemeshow goodness-of-fit test.RESULTS The radiomic nomogram could accurately predict the response of AGC patients to nICT.In the test cohort,the area under curve was 0.893,with a 95%confidence interval of 0.803-0.991.DCA indicated that the clinical application of the radiomic nomogram yielded greater net benefit than alternative models.CONCLUSION A nomogram combining a radiomic signature and a clinical signature was designed to predict the efficacy of nICT in patients with AGC.This tool can assist clinicians in treatment-related decision-making.
基金Supported by The Chinese National Key Research and Development Project,No.2021YFC2500400 and No.2021YFC2500402Tianjin Key Medical Discipline(Specialty)Construction Project,No.TJYXZDXK-009A.
文摘BACKGROUND Gastrointestinal stromal tumors(GIST)are prevalent neoplasm originating from the gastrointestinal mesenchyme.Approximately 50%of GIST patients experience tumor recurrence within 5 years.Thus,there is a pressing need to accurately evaluate risk stratification preoperatively.AIM To assess the application of a deep learning model(DLM)combined with computed tomography features for predicting risk stratification of GISTs.METHODS Preoperative contrast-enhanced computed tomography(CECT)images of 551 GIST patients were retrospectively analyzed.All image features were independently analyzed by two radiologists.Quantitative parameters were statistically analyzed to identify significant predictors of high-risk malignancy.Patients were randomly assigned to the training(n=386)and validation cohorts(n=165).A DLM and a combined DLM were established for predicting the GIST risk stratification using convolutional neural network and subsequently evaluated in the validation cohort.RESULTS Among the analyzed CECT image features,tumor size,ulceration,and enlarged feeding vessels were identified as significant risk predictors(P<0.05).In DLM,the overall area under the receiver operating characteristic curve(AUROC)was 0.88,with the accuracy(ACC)and AUROCs for each stratification being 87%and 0.96 for low-risk,79%and 0.74 for intermediate-risk,and 84%and 0.90 for high-risk,respectively.The overall ACC and AUROC were 84%and 0.94 in the combined model.The ACC and AUROCs for each risk stratification were 92%and 0.97 for low-risk,87%and 0.83 for intermediate-risk,and 90%and 0.96 for high-risk,respectively.Differences in AUROCs for each risk stratification between the two models were significant(P<0.05).CONCLUSION A combined DLM with satisfactory performance for preoperatively predicting GIST stratifications was developed using routine computed tomography data,demonstrating superiority compared to DLM.
基金Supported by Health Commission of Shanxi Province,No.2021XM39.
文摘BACKGROUND Percutaneous endoscopic lumbar decompression(PELD)shows promise for lumbar spinal stenosis(LSS)treatment,but its use is limited by the disease's complexity and procedural challenges.AIM In this study,the effects of preoperative planning and intraoperative guidance with computed tomography(CT)/magnetic resonance imaging(MRI)registration techniques on PELD for LSS and postoperative rehabilitation outcomes were evaluated.METHODS This retrospective study was conducted with data from patients who underwent PELD for LSS between January 2021 and December 2023.Patients were assigned to preoperative CT/MRI registration and control groups.Data collected included the operative time,length of hospital stay,visual analog scale(VAS)scores for low back and leg pain,and the Japanese Orthopaedic Association(JOA)lumbar spine score.Differences between groups were assessed using Student’s t test.RESULTS Data from 135 patients(71 in the CT/MRI registration group,64 in the control group)were analyzed.The operative time was significantly shorter in the CT/MRI registration group(P=0.007).At 2 months postoperatively,both groups showed significant reductions in VAS leg and low back pain scores(all P<0.001)and improvements in the JOA score(both P<0.001).No complication or death occurred.Preoperatively,pain and JOA scores were similar between groups(P=0.830,P=0.470,and P=0.287,respectively).At 2 months postoperatively,patients in the CT/MRI registration group reported lower leg and low back pain levels(P<0.001 and P=0.001,respectively)and had higher JOA scores(P=0.004)than did patients in the control group.CONCLUSION Preoperative CT/MRI registration for PELD for LSS reduced the operative time and VAS pain scores at 2 months and improved JOA scores,demonstrating enhanced effectiveness and safety.
文摘X-ray computed tomography(XCT)has recently emerged as a powerful tool for characterizing the evolution of microstructure during phase transformation in three dimensional(3D)such as dendritic solidification of alloys.This paper briefly reviews the recent advances in the in-situ observation of aluminium alloys,magnesium alloys and nickel-based superalloys during solidification using laboratory XCT and synchrotron X-ray sources.The focus is on the growth kinetics of dendrites,porosity and secondary phases.In addition,in-situ characterization during the loading and corrosion process is also discussed.
文摘BACKGROUND Ankle fractures are common lesions of the lower limbs.Approximately 40%of ankle fractures affect the posterior malleolus(PM).Historically,PM osteosynthesis was recommended when PM size in X-ray images was greater than 25%of the joint.Currently,computed tomography(CT)has been gaining traction in the preoperative evaluation of ankle fractures.AIM To elucidate the similarity in dimensions and to correlate PM size in X-ray images with the articular surface of the affected tibial plafond in the axial view on CT(AXCT)of a PM fracture.METHODS Eighty-one patients(mean age:39.4±13.5 years)were evaluated(54.3%were male).Two independent examiners measured PM size in profile X-ray images(PMXR)and sagittal CT(SAGCT)slices.The correlation of the measurements between the examiners and the difference in the PM fragment sizes between the two images were compared.Next,the PM size in PMXR was compared with the surface of the tibial plafond involved in the fracture in AXCT according to the Haraguchi classification.RESULTS The correlation rates between the examiners were 0.93 and 0.94 for PMXR and SAGCT,respectively(P<0.001).Fragments were 2.12%larger in SAGCT than in PMXR(P=0.018).In PMXR,there were 56 cases<25%and 25 cases≥25%.When PMXR was<25%,AXCT corresponded to 10.13%of the tibial plafond.When PMXR was≥25%,AXCT was 24.52%(P<0.001).According to the Haraguchi classification,fracture types I and II had similar PMXR measurements that were greater than those of type III.When analyzing AXCT,a significant difference was found between the three types,with II>I>III(P<0.001).CONCLUSION PM fractures show different sizes using X-ray or CT images.CT showed a larger PM in the sagittal plane and allowed the visualization of the real dimensions of the tibial plafond surface.
文摘BACKGROUND Pancreatic neuroendocrine tumors(NETs)account for about 1%–2%of pancreatic tumors and about 8%of all NETs.Computed tomography(CT),magnetic resonance imaging,and endoscopic ultrasound are common imaging modalities for the diagnosis of pancreatic NETs.Furthermore,somatostatin receptor imaging is of great value for diagnosing pancreatic NETs.Herein,we report the efficacy of technetium-99m methoxy-2-isobutylisonitrile(99mTc-MIBI)single photon emission CT(SPECT)/CT for detecting pancreatic NETs.CASE SUMMARY A 57-year-old woman presented to our hospital with a 1-d history of persistent upper abdominal distending pain.The distending pain in the upper abdomen was aggravated after eating,with nausea and retching.Routine blood test results showed a high neutrophil percentage,low leukomonocyte and monocyte percentages,and low leukomonocyte and eosinophil counts.Amylase,liver and kidney function,and tumor markers alpha-fetoprotein,carcinoembryonic antigen,and cancer antigen(CA)125,CA72-4,CA19-9,and CA153 were normal.Abdominal CT showed a mass,with multiple calcifications between the pancreas and the spleen.The boundary between the mass and the pancreas and spleen was poorly defined.Contrast-enhanced CT revealed that the upper abdominal mass was unevenly and gradually enhanced.99mTc-MIBI SPECT/CT revealed that a focal radioactive concentration,with mild radioactive concentration extending into the upper abdominal mass,was present at the pancreatic body and tail.The 99mTc-MIBI SPECT/CT manifestations were consistent with the final pathological diagnosis of pancreatic NET.CONCLUSION 99mTc-MIBI SPECT/CT appears to be a valuable tool for detecting pancreatic NETs.
文摘Computed tomography(CT)is emerging as a prominent diagnostic modality in the field of cardiovascular imaging.Artificial intelligence(AI)is making significant strides in the field of information technology,the commercial industry,and health care.Machine learning(ML),a branch of AI,can optimize the performance of CT and augment the assessment of coronary artery disease.These ML platforms can automate multiple tasks,perform calculations,and integrate information from a variety of data sources.In this review article,we explore the ML in CT imaging.
基金Supported by the National Natural Science Foundation of China,Nos.61971350,81627807 and 11727813the National Key R&D Program of China,No.2016YFC1300300+3 种基金the China Postdoctoral Science Foundation,No.2019M653717Shaanxi Science Funds for Distinguished Young Scholars,No.2020JC-27Fok Ying Tung Education Foundation,No.161104and Program for the Young Topnotch Talent of Shaanxi Province.
文摘Coronary artery disease(CAD)has become a major illness endangering human health.It mainly manifests as atherosclerotic plaques,especially vulnerable plaques without obvious symptoms in the early stage.Once a rupture occurs,it will lead to severe coronary stenosis,which in turn may trigger a major adverse cardiovascular event.Computed tomography angiography(CTA)has become a standard diagnostic tool for early screening of coronary plaque and stenosis due to its advantages in high resolution,noninvasiveness,and three-dimensional imaging.However,manual examination of CTA images by radiologists has been proven to be tedious and time-consuming,which might also lead to intra-and interobserver errors.Nowadays,many machine learning algorithms have enabled the(semi-)automatic diagnosis of CAD by extracting quantitative features from CTA images.This paper provides a survey of these machine learning algorithms for the diagnosis of CAD in CTA images,including coronary artery extraction,coronary plaque detection,vulnerable plaque identification,and coronary stenosis assessment.Most included articles were published within this decade and are found in the Web of Science.We wish to give readers a glimpse of the current status,challenges,and perspectives of these machine learning-based analysis methods for automatic CAD diagnosis.
基金Supported by Henan Province 2023 Scientific Research Projects Focused on Higher Education Project,China,No.23A320059.
文摘BACKGROUND The preoperative prediction of peritoneal metastasis(PM)in gastric cancer would prevent unnecessary surgery and promptly indicate an appropriate treatment plan.AIM To explore the predictive value of visceral fat(VF)parameters obtained from preoperative computed tomography(CT)images for occult PM and to develop an individualized model for predicting occult PM in patients with gastric carcinoma(GC).METHODS A total of 128 confirmed GC cases(84 male and 44 female patients)that underwent CT scans were analyzed and categorized into PM-positive(n=43)and PM-negative(n=85)groups.The clinical characteristics and VF parameters of two regions of interest(ROIs)were collected.Univariate and stratified analyses based on VF volume were performed to screen for predictive characteristics for occult PM.Prediction models with and without VF parameters were established by multivariable logistic regression analysis.RESULTS The mean attenuations of VF_(ROI 1)and VF_(ROI 2)varied significantly between the PM-positive and PMnegative groups(P=0.044 and 0.001,respectively).The areas under the receiver operating characteristic curves(AUCs)of VF_(ROI 1)and VF_(ROI 2)were 0.599 and 0.657,respectively.The mean attenuation of VF_(ROI 2)was included in the final prediction combined model,but not an independent risk factor of PM(P=0.068).No significant difference was observed between the models with and without mean attenuation of VF(AUC:0.749 vs 0.730,P=0.339).CONCLUSION The mean attenuation of VF is a potential auxiliary parameter for predicting occult PM in patients with GC.
基金Projects(41572277,41877229) supported by the National Natural Science Foundation of ChinaProject(2015A030313118) supported by the Natural Science Foundation of Guangdong Province,ChinaProject(201607010023) supported by the Science and Technology Program of Guangzhou,China
文摘A small problem about soil particle regularization and contacts but essential to geotechnical engineering was studied.The soils sourced from Guangzhou and Xiamen were sieved into five different particle scale ranges(d<0.075 mm,0.075 mm≤d<0.1 mm,0.1 mm≤d<0.2 mm,0.2 mm≤d<0.5 mm and 0.5 mm≤d<1.0 mm)to study the structures and particle contacts of granite residual soil.The X-ray micro computed tomography method was used to reconstruct the microstructure of granite residual soil.The particle was identified and regularized using principal component analysis(PCA).The particle contacts and geometrical characteristics in 3D space were analyzed and summarized using statistical analyses.The results demonstrate that the main types of contact among the particles are face-face,face-angle,face-edge,edge-edge,edge-angle and angle-angle contacts for particle sizes less than 0.2 mm.When the particle sizes are greater than 0.2 mm,the contacts are effectively summarized as face-face,face-angle,face-edge,edge-edge,edge-angle,angle-angle,sphere-sphere,sphere-face,sphere-edge and sphere-angle contacts.The differences in porosity among the original sample,reconstructed sample and regularized sample are closely related to the water-swelling and water-disintegrable characteristics of granite residual soil.
基金financially supported by the National Natural Science Foundation of China(No.51304076)the Natural Science Foundation of Hunan Province,China(No.14JJ4064)
文摘Mineral dissemination and pore space distribution in ore particles are important features that influence heap leaching performance. To quantify the mineral dissemination and pore space distribution of an ore particle, a cylindrical copper oxide ore sample (I center dot 4.6 mm x 5.6 mm) was scanned using high-resolution X-ray computed tomography (HRXCT), a nondestructive imaging technology, at a spatial resolution of 4.85 mu m. Combined with three-dimensional (3D) image analysis techniques, the main mineral phases and pore space were segmented and the volume fraction of each phase was calculated. In addition, the mass fraction of each mineral phase was estimated and the result was validated with that obtained using traditional techniques. Furthermore, the pore phase features, including the pore size distribution, pore surface area, pore fractal dimension, pore centerline, and the pore connectivity, were investigated quantitatively. The pore space analysis results indicate that the pore size distribution closely fits a log-normal distribution and that the pore space morphology is complicated, with a large surface area and low connectivity. This study demonstrates that the combination of HRXCT and 3D image analysis is an effective tool for acquiring 3D mineralogical and pore structural data.
基金supported by the National Natural Science Foundation of China (Grant Nos. 12102312 and 41372314)State Key Laboratory of Geohazard Prevention and Geoenvironment Protection Open Foundation, Chengdu University of Technology, China (Grant No. SKLGP2021K011)
文摘Due to seasonal climate alterations,the microstructure and permeability of granite residual soil are easily affected by multiple dry-wet cycles.The X-ray micro computed tomography(micro-CT)acted as a nondestructive tool for characterizing the microstructure of soil samples exposed to a range of damage levels induced by dry-wet cycles.Subsequently,the variations of pore distribution and permeability due to drywet cycling effects were revealed based on three-dimensional(3D)pore distribution analysis and seepage simulations.According to the results,granite residual soils could be separated into four different components,namely,pores,clay,quartz,and hematite,from micro-CT images.The reconstructed 3D pore models dynamically demonstrated the expanding and connecting patterns of pore structures during drywet cycles.The values of porosity and connectivity are positively correlated with the number of dry-wet cycles,which were expressed by exponential and linear functions,respectively.The pore volume probability distribution curves of granite residual soil coincide with the χ^(2)distribution curve,which verifies the effectiveness of the assumption of χ^(2)distribution probability.The pore volume distribution curves suggest that the pores in soils were divided into four types based on their volumes,i.e.micropores,mesopores,macropores,and cracks.From a quantitative and visual perspective,considerable small pores are gradually transformed into cracks with a large volume and a high connectivity.Under the action of dry-wet cycles,the number of seepage flow streamlines which contribute to water permeation in seepage simulation increases distinctly,as well as the permeability and hydraulic conductivity.The calculated hydraulic conductivity is comparable with measured ones with an acceptable error margin in general,verifying the accuracy of seepage simulations based on micro-CT results.
基金Funded by the National Natural Science Foundation of China(No.51072035),the Ph D Program’s Foundation of Ministry of Education of China(No.20090092110029)the Research Innovation Program for College Graduates of Jiangsu Province(No.CXZZ_0145)the Scientific Research Foundation of Graduate School of Southeast University(Nos.YBJJ1127 and YBPY1208)
文摘The bio-sandstone, which was cemented by microbe cement, was firstly prepared, and then the microstructure evolution process was studied by X-ray computed tomography （X-CT） technique. The experimental results indicate that the microstructure of bio-sandstone becomes dense with the development of age. The evolution of inner structure at different positions is different due to the different contents of microbial induced precipitation calcite. Besides, the increase rate of microbial induced precipitation calcite gradually decreases because of the reduction of microbe absorption content with the decreasing pore size in bio-sandstone.
文摘As healthcare professionals continue to combat the coronavirus disease 2019(COVID-19)infection worldwide,there is an increasing interest in the role of imaging and the relevance of various modalities.Since imaging not only helps assess the disease at the time of diagnosis but also aids evaluation of response to management,it is critical to examine the role of different modalities currently in use,such as baseline X-rays and computed tomography scans carefully.In this article,we will draw attention to the critical findings for the radiologist.Further,we will look at point of care ultrasound,an increasingly a popular tool in diagnostic medicine,as a component of COVID-19 management.
基金financially supported by the National Science Foundation of China-Yunnan Joint Fund(U1502232)the Natural Science Foundation of Yunnan Province(2014FD007)the Natural Science Foundation of Kunming University of Science and Technology(KKSY201406009)
文摘The three dimensional （3D） geometry of soil macropores largely controls preferential flow, which is a significant infiltrating mechanism for rainfall in forest soils and affects slope stability. However, detailed studies on the 3D geometry of macropore networks in forest soils are rare. The intense rainfall-triggered potentially unstable slopes were threatening the villages at the downstream of Touzhai valley （Yunnan, China）. We visualized and quantified the 3D macropore networks in undisturbed soil columns （Histosols） taken from a forest hillslope in Touzhai valley, and compared them with those in agricultural soils （corn and soybean in USA; barley, fodder beet and red fescue in Denmark） and grassland soils in USA. We took two large undisturbed soil columns （250 mm^25o mmxsoo mm）, and scanned the soil columns at in-situ soil water content conditions using X-ray computed tomography at a voxel resolution of 0.945 × 0.945 × 1.500o mm^3. After reconstruction and visualization, we quantified the characteristics of macropore networks. In the studied forest soils, the main types of maeropores were root channels, inter-aggregate voids, maeropores without knowing origin, root-soil interfaee and stone-soil interface. While maeropore networks tend to be more eomplex, larger, deeper and longer. The forest soils have high maeroporosity, total maeropore wall area density, node density, and large maeropore volume, hydraulie radius, mean maeropore length, angle, and low tortuosity. The findings suggest that maeropore networks in the forest soils have high inter- connectivity, vertical continuity, linearity and less vertically oriented.
